{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# 决策树可视化展示"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "6673a9c6bc3c9781"
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "# 1. 导入依赖\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T07:09:02.452638500Z",
     "start_time": "2024-05-06T07:09:02.004350200Z"
    }
   },
   "id": "2c57961d99eb242d"
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "outputs": [],
   "source": [
    "# 2. 读取数据集（莺尾花数据集）\n",
    "from sklearn.datasets import load_iris\n",
    "iris = load_iris()\n",
    "X = iris.data[:, 2:]    # 所有行+前两列（2/3）\n",
    "y = iris.target"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:51:47.481530Z",
     "start_time": "2024-05-06T08:51:47.467518800Z"
    }
   },
   "id": "a6f441800a0343b2"
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "outputs": [
    {
     "data": {
      "text/plain": "DecisionTreeClassifier(max_depth=2)",
      "text/html": "<style>#sk-container-id-3 {\n  /* Definition of color scheme common for light and dark mode */\n  --sklearn-color-text: black;\n  --sklearn-color-line: gray;\n  /* Definition of color scheme for unfitted estimators */\n  --sklearn-color-unfitted-level-0: #fff5e6;\n  --sklearn-color-unfitted-level-1: #f6e4d2;\n  --sklearn-color-unfitted-level-2: #ffe0b3;\n  --sklearn-color-unfitted-level-3: chocolate;\n  /* Definition of color scheme for fitted estimators */\n  --sklearn-color-fitted-level-0: #f0f8ff;\n  --sklearn-color-fitted-level-1: #d4ebff;\n  --sklearn-color-fitted-level-2: #b3dbfd;\n  --sklearn-color-fitted-level-3: cornflowerblue;\n\n  /* Specific color for light theme */\n  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n  --sklearn-color-icon: #696969;\n\n  @media (prefers-color-scheme: dark) {\n    /* Redefinition of color scheme for dark theme */\n    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n    --sklearn-color-icon: #878787;\n  }\n}\n\n#sk-container-id-3 {\n  color: var(--sklearn-color-text);\n}\n\n#sk-container-id-3 pre {\n  padding: 0;\n}\n\n#sk-container-id-3 input.sk-hidden--visually {\n  border: 0;\n  clip: rect(1px 1px 1px 1px);\n  clip: rect(1px, 1px, 1px, 1px);\n  height: 1px;\n  margin: -1px;\n  overflow: hidden;\n  padding: 0;\n  position: absolute;\n  width: 1px;\n}\n\n#sk-container-id-3 div.sk-dashed-wrapped {\n  border: 1px dashed var(--sklearn-color-line);\n  margin: 0 0.4em 0.5em 0.4em;\n  box-sizing: border-box;\n  padding-bottom: 0.4em;\n  background-color: var(--sklearn-color-background);\n}\n\n#sk-container-id-3 div.sk-container {\n  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n     but bootstrap.min.css set `[hidden] { display: none !important; }`\n     so we also need the `!important` here to be able to override the\n     default hidden behavior on the sphinx rendered scikit-learn.org.\n     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n  display: inline-block !important;\n  position: relative;\n}\n\n#sk-container-id-3 div.sk-text-repr-fallback {\n  display: none;\n}\n\ndiv.sk-parallel-item,\ndiv.sk-serial,\ndiv.sk-item {\n  /* draw centered vertical line to link estimators */\n  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n  background-size: 2px 100%;\n  background-repeat: no-repeat;\n  background-position: center center;\n}\n\n/* Parallel-specific style estimator block */\n\n#sk-container-id-3 div.sk-parallel-item::after {\n  content: \"\";\n  width: 100%;\n  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n  flex-grow: 1;\n}\n\n#sk-container-id-3 div.sk-parallel {\n  display: flex;\n  align-items: stretch;\n  justify-content: center;\n  background-color: var(--sklearn-color-background);\n  position: relative;\n}\n\n#sk-container-id-3 div.sk-parallel-item {\n  display: flex;\n  flex-direction: column;\n}\n\n#sk-container-id-3 div.sk-parallel-item:first-child::after {\n  align-self: flex-end;\n  width: 50%;\n}\n\n#sk-container-id-3 div.sk-parallel-item:last-child::after {\n  align-self: flex-start;\n  width: 50%;\n}\n\n#sk-container-id-3 div.sk-parallel-item:only-child::after {\n  width: 0;\n}\n\n/* Serial-specific style estimator block */\n\n#sk-container-id-3 div.sk-serial {\n  display: flex;\n  flex-direction: column;\n  align-items: center;\n  background-color: var(--sklearn-color-background);\n  padding-right: 1em;\n  padding-left: 1em;\n}\n\n\n/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\nclickable and can be expanded/collapsed.\n- Pipeline and ColumnTransformer use this feature and define the default style\n- Estimators will overwrite some part of the style using the `sk-estimator` class\n*/\n\n/* Pipeline and ColumnTransformer style (default) */\n\n#sk-container-id-3 div.sk-toggleable {\n  /* Default theme specific background. It is overwritten whether we have a\n  specific estimator or a Pipeline/ColumnTransformer */\n  background-color: var(--sklearn-color-background);\n}\n\n/* Toggleable label */\n#sk-container-id-3 label.sk-toggleable__label {\n  cursor: pointer;\n  display: block;\n  width: 100%;\n  margin-bottom: 0;\n  padding: 0.5em;\n  box-sizing: border-box;\n  text-align: center;\n}\n\n#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n  /* Arrow on the left of the label */\n  content: \"▸\";\n  float: left;\n  margin-right: 0.25em;\n  color: var(--sklearn-color-icon);\n}\n\n#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n  color: var(--sklearn-color-text);\n}\n\n/* Toggleable content - dropdown */\n\n#sk-container-id-3 div.sk-toggleable__content {\n  max-height: 0;\n  max-width: 0;\n  overflow: hidden;\n  text-align: left;\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-0);\n}\n\n#sk-container-id-3 div.sk-toggleable__content.fitted {\n  /* fitted */\n  background-color: var(--sklearn-color-fitted-level-0);\n}\n\n#sk-container-id-3 div.sk-toggleable__content pre {\n  margin: 0.2em;\n  border-radius: 0.25em;\n  color: var(--sklearn-color-text);\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-0);\n}\n\n#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n  /* unfitted */\n  background-color: var(--sklearn-color-fitted-level-0);\n}\n\n#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n  /* Expand drop-down */\n  max-height: 200px;\n  max-width: 100%;\n  overflow: auto;\n}\n\n#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n  content: \"▾\";\n}\n\n/* Pipeline/ColumnTransformer-specific style */\n\n#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n  color: var(--sklearn-color-text);\n  background-color: var(--sklearn-color-unfitted-level-2);\n}\n\n#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n  background-color: var(--sklearn-color-fitted-level-2);\n}\n\n/* Estimator-specific style */\n\n/* Colorize estimator box */\n#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-2);\n}\n\n#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n  /* fitted */\n  background-color: var(--sklearn-color-fitted-level-2);\n}\n\n#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n#sk-container-id-3 div.sk-label label {\n  /* The background is the default theme color */\n  color: var(--sklearn-color-text-on-default-background);\n}\n\n/* On hover, darken the color of the background */\n#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n  color: var(--sklearn-color-text);\n  background-color: var(--sklearn-color-unfitted-level-2);\n}\n\n/* Label box, darken color on hover, fitted */\n#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n  color: var(--sklearn-color-text);\n  background-color: var(--sklearn-color-fitted-level-2);\n}\n\n/* Estimator label */\n\n#sk-container-id-3 div.sk-label label {\n  font-family: monospace;\n  font-weight: bold;\n  display: inline-block;\n  line-height: 1.2em;\n}\n\n#sk-container-id-3 div.sk-label-container {\n  text-align: center;\n}\n\n/* Estimator-specific */\n#sk-container-id-3 div.sk-estimator {\n  font-family: monospace;\n  border: 1px dotted var(--sklearn-color-border-box);\n  border-radius: 0.25em;\n  box-sizing: border-box;\n  margin-bottom: 0.5em;\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-0);\n}\n\n#sk-container-id-3 div.sk-estimator.fitted {\n  /* fitted */\n  background-color: var(--sklearn-color-fitted-level-0);\n}\n\n/* on hover */\n#sk-container-id-3 div.sk-estimator:hover {\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-2);\n}\n\n#sk-container-id-3 div.sk-estimator.fitted:hover {\n  /* fitted */\n  background-color: var(--sklearn-color-fitted-level-2);\n}\n\n/* Specification for estimator info (e.g. \"i\" and \"?\") */\n\n/* Common style for \"i\" and \"?\" */\n\n.sk-estimator-doc-link,\na:link.sk-estimator-doc-link,\na:visited.sk-estimator-doc-link {\n  float: right;\n  font-size: smaller;\n  line-height: 1em;\n  font-family: monospace;\n  background-color: var(--sklearn-color-background);\n  border-radius: 1em;\n  height: 1em;\n  width: 1em;\n  text-decoration: none !important;\n  margin-left: 1ex;\n  /* unfitted */\n  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n  color: var(--sklearn-color-unfitted-level-1);\n}\n\n.sk-estimator-doc-link.fitted,\na:link.sk-estimator-doc-link.fitted,\na:visited.sk-estimator-doc-link.fitted {\n  /* fitted */\n  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n  color: var(--sklearn-color-fitted-level-1);\n}\n\n/* On hover */\ndiv.sk-estimator:hover .sk-estimator-doc-link:hover,\n.sk-estimator-doc-link:hover,\ndiv.sk-label-container:hover .sk-estimator-doc-link:hover,\n.sk-estimator-doc-link:hover {\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-3);\n  color: var(--sklearn-color-background);\n  text-decoration: none;\n}\n\ndiv.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n.sk-estimator-doc-link.fitted:hover,\ndiv.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n.sk-estimator-doc-link.fitted:hover {\n  /* fitted */\n  background-color: var(--sklearn-color-fitted-level-3);\n  color: var(--sklearn-color-background);\n  text-decoration: none;\n}\n\n/* Span, style for the box shown on hovering the info icon */\n.sk-estimator-doc-link span {\n  display: none;\n  z-index: 9999;\n  position: relative;\n  font-weight: normal;\n  right: .2ex;\n  padding: .5ex;\n  margin: .5ex;\n  width: min-content;\n  min-width: 20ex;\n  max-width: 50ex;\n  color: var(--sklearn-color-text);\n  box-shadow: 2pt 2pt 4pt #999;\n  /* unfitted */\n  background: var(--sklearn-color-unfitted-level-0);\n  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n}\n\n.sk-estimator-doc-link.fitted span {\n  /* fitted */\n  background: var(--sklearn-color-fitted-level-0);\n  border: var(--sklearn-color-fitted-level-3);\n}\n\n.sk-estimator-doc-link:hover span {\n  display: block;\n}\n\n/* \"?\"-specific style due to the `<a>` HTML tag */\n\n#sk-container-id-3 a.estimator_doc_link {\n  float: right;\n  font-size: 1rem;\n  line-height: 1em;\n  font-family: monospace;\n  background-color: var(--sklearn-color-background);\n  border-radius: 1rem;\n  height: 1rem;\n  width: 1rem;\n  text-decoration: none;\n  /* unfitted */\n  color: var(--sklearn-color-unfitted-level-1);\n  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n}\n\n#sk-container-id-3 a.estimator_doc_link.fitted {\n  /* fitted */\n  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n  color: var(--sklearn-color-fitted-level-1);\n}\n\n/* On hover */\n#sk-container-id-3 a.estimator_doc_link:hover {\n  /* unfitted */\n  background-color: var(--sklearn-color-unfitted-level-3);\n  color: var(--sklearn-color-background);\n  text-decoration: none;\n}\n\n#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n  /* fitted */\n  background-color: var(--sklearn-color-fitted-level-3);\n}\n</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=2)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=2)</pre></div> </div></div></div></div>"
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3. 使用sklearn中的决策树分类器训练模型\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "clf = DecisionTreeClassifier(max_depth=2)\n",
    "clf.fit(X, y)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:51:48.701504700Z",
     "start_time": "2024-05-06T08:51:48.687991700Z"
    }
   },
   "id": "6a0092b380432a91"
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "outputs": [],
   "source": [
    "# 4. 可视化展示决策树\n",
    "from sklearn.tree import export_graphviz\n",
    "export_graphviz(\n",
    "    clf, \n",
    "    out_file='iris_tree.dot', \n",
    "    feature_names=iris.feature_names[2:], \n",
    "    class_names=iris.target_names, \n",
    "    rounded=True, \n",
    "    filled=True\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:51:49.933313700Z",
     "start_time": "2024-05-06T08:51:49.924310Z"
    }
   },
   "id": "c7da0b3c439f6859"
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": "<IPython.core.display.Image object>"
     },
     "execution_count": 46,
     "metadata": {
      "image/png": {
       "width": 800,
       "height": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 5. 打开命令行输入命令：dot -Tpng iris_tree.dot -o iris_tree.png\n",
    "# 6. 查看png图像\n",
    "from IPython.display import Image\n",
    "Image(filename='iris_tree.png',width=800,height=600)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:51:51.182196400Z",
     "start_time": "2024-05-06T08:51:51.171193200Z"
    }
   },
   "id": "e559502f4964c8e"
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 决策树概率估计"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "dd076054b81fcb6e"
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[0.        , 0.02173913, 0.97826087]])"
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict([[1.5,2.0]])    # 预测输入数据属于哪一类\n",
    "clf.predict_proba([[1.5,2.0]])    # 预测输入数据属于各类概率\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:51:53.076925Z",
     "start_time": "2024-05-06T08:51:53.048925800Z"
    }
   },
   "id": "736deca437aab99c"
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 决策边界展示"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "e30cefc0d7bdc5b2"
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x600 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "def plot_decision_boundary(plt, clf, X , y,axes=[0,7.5,0,3],iris=True):\n",
    "    x1s = np.linspace(axes[0],axes[1],100)\n",
    "    x2s = np.linspace(axes[2],axes[3],100)\n",
    "    x1,x2 = np.meshgrid(x1s,x2s)    # 生成网格坐标,平面所有点\n",
    "    X_new = np.c_[x1.ravel(),x2.ravel()]\n",
    "    y_pred = clf.predict(X_new).reshape(x1.shape)    # 预测网格坐标属于哪一类\n",
    "    custom_cmap = ListedColormap(['#fafab0','#9898ff','#a0faa0'])\n",
    "    plt.contourf(x1,x2,y_pred,alpha=0.3,cmap=custom_cmap)    # 绘制决策边界\n",
    "    plt.plot(X[:,0][y==0],X[:,1][y==0],'yo',label='Iris-Setosa')    # 绘制Iris-Setosa点\n",
    "    plt.plot(X[:,0][y==1],X[:,1][y==1],'bs',label='Iris-Versicolor')    # 绘制Iris-Versicolor点\n",
    "    plt.plot(X[:,0][y==2],X[:,1][y==2],'g^',label='Iris-Virginica')    # 绘制Iris-Virginica点\n",
    "    plt.axis(axes)\n",
    "    if iris:\n",
    "        plt.xlabel('Petal length')\n",
    "        plt.ylabel('Petal width')\n",
    "    plt.legend(loc='lower right')\n",
    "    \n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "plot_decision_boundary(plt,clf,X,y)\n",
    "plt.show()\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:53:01.448324600Z",
     "start_time": "2024-05-06T08:53:01.353783100Z"
    }
   },
   "id": "cba9ac43f8ace174"
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 决策树初始化参数作用"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "1822ed9f9080d38d"
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1200x400 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. 创建数据\n",
    "from sklearn.datasets import make_moons\n",
    "X, y = make_moons(n_samples=100, noise=0.4, random_state=0)\n",
    "\n",
    "# 2. 创建模型， 对比参数:min_samples_leaf：叶子节点最少样本数，如果一个节点的样本数小于这个值，那么这个节点就不再分裂\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "clf_0 = DecisionTreeClassifier()\n",
    "clf_0.fit(X, y)\n",
    "clf_1 = DecisionTreeClassifier(min_samples_leaf=5)\n",
    "clf_1.fit(X, y)\n",
    "\n",
    "# 3. 可视化展示\n",
    "plt.figure(figsize=(12,4))\n",
    "plt.subplot(121)\n",
    "plot_decision_boundary(plt,clf_0,X,y,axes=[-1.5,2.5,-1,1.5],iris=False)\n",
    "plt.title('no restriction')\n",
    "plt.subplot(122)\n",
    "plot_decision_boundary(plt,clf_1,X,y,axes=[-1.5,2.5,-1,1.5],iris=False)\n",
    "plt.title('min_samples_leaf=4')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T08:54:13.011593900Z",
     "start_time": "2024-05-06T08:54:12.792317200Z"
    }
   },
   "id": "2f32021cb4e628c7"
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 数据集对决策树的影响"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "f5666ef462236c3c"
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1200x600 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. 创建数据\n",
    "np.random.seed(42)\n",
    "X_0 = np.random.rand(100,2)-0.5\n",
    "y = (X[:,0]>0).astype(np.float32)*2\n",
    "\n",
    "# 2. 对数据进行旋转\n",
    "angle = np.pi/4\n",
    "rotation_matrix = np.array([[np.cos(angle), -np.sin(angle)],[np.sin(angle), np.cos(angle)]])\n",
    "X_1 = np.dot(X_0, rotation_matrix)\n",
    "\n",
    "# 3. 创建模型,并训练数据\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "clf_0 = DecisionTreeClassifier(random_state=42,max_depth=2)\n",
    "clf_0.fit(X_0, y)\n",
    "clf_1 = DecisionTreeClassifier(random_state=42,max_depth=2)\n",
    "clf_1.fit(X_1, y)\n",
    "\n",
    "# 4. 可视化展示\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.subplot(121)\n",
    "plot_decision_boundary(plt,clf_0,X_0,y,axes=[-0.7,0.7,-0.7,0.7],iris=False)\n",
    "plt.title('original data')\n",
    "plt.subplot(122)\n",
    "plot_decision_boundary(plt,clf_1,X_1,y,axes=[-0.7,0.7,-0.7,0.7],iris=False)\n",
    "plt.title('rotated data')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T09:14:27.095086400Z",
     "start_time": "2024-05-06T09:14:26.895587Z"
    }
   },
   "id": "8f5b3e03fab74b1d"
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 决策树完成回归任务"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "63aa0e2873a2f156"
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1200x600 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. 创建数据\n",
    "np.random.seed(42)\n",
    "m = 200\n",
    "X = np.random.rand(m,1)\n",
    "y = 4*(X-0.5)**2\n",
    "y = y + np.random.randn(m,1)/10  # 加入噪声\n",
    "\n",
    "# 2. 创建模型,并训练数据 \n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "regr_1 = DecisionTreeRegressor(max_depth=2,random_state=42)\n",
    "regr_2 = DecisionTreeRegressor(max_depth=5,random_state=42)\n",
    "regr_1.fit(X,y)\n",
    "regr_2.fit(X,y)\n",
    "\n",
    "# 3. 可视化展示\n",
    "X_test = np.linspace(0,1,500).reshape(-1,1)\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.subplot(121)\n",
    "plt.plot(X,y,'b.')\n",
    "plt.plot(X_test,regr_1.predict(X_test),'r-')\n",
    "plt.title('max_depth=2')\n",
    "plt.subplot(122)\n",
    "plt.plot(X,y,'b.')\n",
    "plt.plot(X_test,regr_2.predict(X_test),'r-')\n",
    "plt.title('max_depth=5')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-05-06T09:24:01.858000700Z",
     "start_time": "2024-05-06T09:24:01.696042900Z"
    }
   },
   "id": "d969dae4739aee8e"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "24844909f8156214"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "777df9c0f0d0447e"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "c1371d22906c25b7"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "12b25817a34da8e7"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "f2a2f791963c9e6e"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "5b9e63f006a388a0"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "f6d3108e6776fae7"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "b01a0ba505acaebb"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
